Abstract

Purpose

Latent class analysis (LCA), a statistical method for identifying latent classes within a population using multiple indicators, has been used to study the heterogeneity of health among the elderly. We aim to identify health status profiles of older adults using LCA and examine the socio-demographic characteristics associated with each profile.

Methods

A community health survey of residents ≥60 years was conducted in Marine Parade, Singapore. We performed LCA on seven health indicators (number of chronic conditions, activities of daily living (ADL) dependency, pain, depression, cognition, social isolation, and frequency of socialising) to identify distinct classes of health status profiles. Multivariable logistic regression was conducted to examine the socio-demographic characteristics associated with each profile.

Conclusion

Using LCA, we identified two distinct health status profiles which accounted for the heterogeneity of the elderly population. Selected socio-demographic characteristics were associated with different profiles and provide implications for the structuring of future public health interventions targeting the older population.

Tomaka, J., Thompson, S., & Palacios, R. (2006). The relation of social isolation, loneliness, and social support to disease outcomes among the elderly.
Journal of Aging and Health,18(3), 359–384.
PubMedCrossRef

Quality of Life Research
An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation - An Official Journal of the International Society of Quality of Life Research
Ausgabe 10/2014
Print ISSN: 0962-9343
Elektronische ISSN: 1573-2649